Artificial Intelligence (AI) in Dental Age Estimation Studies: A Scientometric Analysis

• Published in: INTELIGENCIA ARTIFICIAL-IBEROAMERICAN JOURNAL OF ARTIFICIAL INTELLIGENCE
• Main Authors: Zainuddin, Muhammad Zaid; Azizan, Azliyana; Yusof, Mohd Yusmiaidil Putera Mohd
• Format: Article
• Language: English
• Published: ASOC ESPANOLA INTELIGENCIA ARTIFICIAL 2025
• Subjects: Computer Science
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001409625300001
• ISSN: 1137-3601; 1988-3064
• DOI: 10.4114/intartif.vol28iss75pp101-113

Dental age estimation (DAE) is important in age-related studies ranging from forensics, clinical dentistry and bioanthropology. DAE heavily relies on image analysis and morphometrics and has underwent academic scrutiny to improve its level of reliability and accuracy. The recent rise of artificial intelligence (AI) in data analysis allows accurate analysis without the influence of human error. As AI has penetrated DAE research, there is a lack of scientometric analysis regarding AI-driven DAE studies. This scientometric study presents an analysis of AI-driven DAE research based on data from the Scopus and Web of Science literature databases. This study examines various parameters, such as publication trends, prolific countries and research institutions, active journals and highly cited publications as well as highly used keywords pertaining to AI-driven DAE studies. Notably, though the niche area is fairly recent, there has been a substantial increase in the number of publications in AI-driven DAE research in the past few years. Countries such as China, Malaysia and South Korea are currently at the forefront of publications on the application of AI in DAE studies. This study also finds that a variety of journals ranging from dentistry, law, forensics and computer science are publishing studies keywords were amongst the dominant keywords used. This scientometric analysis provides an overview of studies and may help identify possible research gaps.